Archive for the ‘geographic information systems’ Category

PPGIS Literature & Framework

Sunday, September 24th, 2017

The idea of PPGIS may appear relatively abstract when compared to the run-of-the-mill public participation (PP) process but at its core it is striving to accomplish the same thing. It is unbiasedly taking stakeholders into consideration for projects by giving them all the same information they would have in a regular PP process but with the addition of a simple (in most cases) geovisualization/spatial representation. This provides the stakeholder with perspective/insight that potentially could have been overlooked.

As noted in the article, PPGIS has grown to cover an extensive range of applications. As the technology changes and individual projects differ so does the PPGIS process. This left me with a more abstract understanding of these projects than I would have liked. It left me intrigued by the possibility of projects; what does a basic but useful geographic information system consist of that translates useful information from layman to the experts. The author includes brief and vague examples of interfaces that left me curious to find out more. Considering the purpose and nature of the article, this general coverage of case examples was definitely sufficient.

Throughout the article, the abstractness of the concept of PPGIS fades away; because it is highly interdisciplinary and has changed so much over time, attempting to define PPGIS is confusing. it was only later in the article that I began to fully understand what a PPGIS project really was/could be.

Regarding the age of the article (11 years (published in 2006)), I would be disappointed to find out that great strides had not been made in this field. The prevalence of natural user interface devices available now (e.g. iPad’s & smartphones) have effectively expanded the amount of potential participants for PPGIS projects. With proper software, intuitive and efficient PPGIS programs and systems could provide more comprehensive participation and ideally more successful projects.

Goodchild Discusses GIS

Sunday, September 17th, 2017

Goodchild’s article presents a brief history of GIScience, and discuses from his perspective, and from the perspectives of others, the role of GIS as well as its label as a science. It is important to note that the article leans more towards an opinion piece or a discussion rather than an objective paper to explore questions without reaching any specific conclusion; however, Goodchild does conclude by making the argument that GIScience is well established as a domain of science without risk of being absorbed into related disciplines. Effectively, Goodchild makes claims that are logical and well founded but seems to forget that the conclusions he pulls are framed within an opinion text.

I enjoyed that the other was careful to make the distinction that the arguments made are from a personal perspective. Naturally the article becomes subject to bias; that of a geographer. Personally, I found the article to be convincing and I agree with the statements made while also remaining open and critical about them. The author’s willingness to explore opposing perspectives translates well to the reader and encourages them to do the same. On the other hand, this creates some confusion and makes it more difficult to finish the reading with a firm conclusion of your own.

The lack of clarity regarding the nature of the paper encourage the reader to explore the subject further and pull their own conclusions. I think to be able to better answer the question of whether or not GIS is a proper ‘science’ could be better explored by comparing/contrasting GIS to other fields of science. While interesting, a more in-depth discussion of what counts as ‘science’ is not the primary subject of the paper and could abstract from the rest of the text.

Why the “Tool or Science” Debate Doesn’t Matter

Sunday, September 17th, 2017

The article by Wright et al. discusses how GIS should be recognized and in doing so considers multiple perspectives: what is science, what is GIS, philosophical schools of knowledge and science, the field of geography as a whole, the labels that GIS could be given, as well as why the label matters.

Effectively, I think that the article reinforced my lack of opinion surrounding the question “GIS: tool or science?”. By introducing fine detail and logical arguments supporting both sides of the debate it makes it harder to reach a conclusion. This discussion reminds me of earth system modelling problems; the main ideas can be reduced and simplified to establish a basic system with one or two inputs and outputs each. Regarding GIS, if we use simple definitions for our terms, it is easy to formulate one’s opinion of what GIS is (science vs tool). However, once we try to get further insight, problems of complexity come into play. An earth system model that strives to account for every individual micro-system within the macro-system quickly becomes too complex. in my opinion, that is, to a certain extent, what Wright’s paper accomplished in my understanding off the debate. I now find that it is harder than ever to decide which arguments are the most legitimate as a result of all the contrast. These arguments are not subject to a ‘right’- ‘wrong’/ ‘valid’ – ‘invalid’ position and this leaves the debate open.

But, unlike the earth system example where intricacies add accuracy to the model, examining the intricacies of this debate do not improve results. As I was reading, I asked myself the question “why does this debate even matter?”. If using GIS as a tool or science allows users to gain insight into our world, what matters should be the discoveries themselves; not the debate over the label of science. After turning the page and seeing the section labeled “Why Does Science Matter?”, I felt like I wasn’t going to be getting the answers I might have hoped for. The author makes the claim that the role of science does matter. This claim, although passive, leads me to believe that the author believes that the ‘Science’ label is important to him and the legitimacy of the field. However, the legitimacy of GIS related discoveries and theories should be founded in their truth, accuracy, and acceptance of peer. Even though interesting, the debate over the label of “Science”, does not improve nor degrade the quality and usefulness of the results of any GIS related project.

Thebault-Spieker: Whose Crowdsourced Market?

Monday, November 30th, 2015

The authors situate mobile crowdsourcing markets such as TaskRabbit within geography, arguing that the geographical perspective is fundamental to the functioning of these markets. I was surprised by how little distance seemed to affect willingness to do a task: the authors write that workers were 4.3% less likely to do a task an hour away than one in their immediate area. To me, an hour seems far, and I thought that this distance would have much more of an impact on willingness. I was also surprised by how much gender impacted the decision to complete a task: the mean of means for women’s willingness to do a task was 20% lower than the mean of means for men. The authors hint at it, but I am curious to know what the demographics are of the people asking for the job to be done.

Overall, I think that this article, and the crowdsourced market, is a good example of an application that needs geography. This is certainly a technology that is embedded in geography, and an analysis like this, I would argue, is really essential to understanding the demographics and the processes behind crowdsourcing applications like this one. Inevitably, some people will look at applications like this, and add them to lists such as “ways to make money in GIS” or “another new innovation that uses GIS!” (I’m looking at you, keynote speaker at GIS day.) However, we need to keep working on critical research, keep asking who these technologies empower, and keep examining the underlying inequalities and how they may be perpetuated by services like this.



Paging Agent Monkey

Sunday, September 21st, 2014

Applications of GIScience are widespread, this is in part due to the fact that every event or process, involving objects or beings has a spatial element in the storyline. Emergent Group Level Navigation: An Agent Based Evaluation of Movement Patterns in a Folivorous Primate (Bonnell et al., 2013) uses GIS to model the movements of primates will the goal of gaining a better understanding of their movement strategy as they forage for food. This is achieved by comparing 12 combinations of collective behaviour against observed moments tracked in the field. Therein demonstrating the power of GIS to not only represent reality, but also simulate it – and in this case bringing the two together.

While an innovative use of technology, I feel there is much more work to be done to further such research. As all models can be defined as ‘a [mere] substitute for a real system’ I’d be cautious in criticizing the small pool of strategy hypothesis presented as too simplistic. I applaud the researchers’ audacious attempt to model such a complex system, living creatures are wildly unpredictable. I would argue that modeling human movements and interactions would offer more insight as most of us carry tracking devices (smart phones) and so many of our transactions feeding or otherwise can be tracked electronically and spatially. The added benefit would be in that one could supplement the research by interviewing a sample of those tracked – we can’t quite talk to monkeys just yet.

I ask: “Why we need to understand monkey movements?” The paper does however point to how such a comprehension sheds light on the cognitive functions of the observed agents, telling us much about how their memory works. This alone leaves this project as one of the most creative uses of GIS. 10/10!

– Othello

Placing GIS in a box: Wright or Wrong?

Sunday, September 7th, 2014

We naturally gravitate towards labeling things, placing them in categories so as to make our world a more organized and orderly one and GIS (geographic information systems) are no exception to this way of thinking. In the article titled “GIS: Tool or Science?” Wright et. al, address the “ambiguity of GIS as a tool or as a science”, introducing in third position of GIS as a toolmaker with advancements in capabilities and usability.

Albeit a trivial question, it speaks to the identity crisis GIS and its practitioners may have experienced in its early years, and even still today. The implications of whether GIS is a tool, tool-maker or a science are wide spread. Most noticeably for the quest for academic legitimacy of GIS as a science – as a student without this legitimacy what place does my GIS-related or GIS-driven research have, if any?

It was a sound article that effectively introduced the three positions. I feel it lent itself more as prompt to engage the reader in the on-going conversation sparked by the online forum discussion that tackled the issue back in 1993. A lot can happen in 20 years, I do wonder what would the GIS community and others would have to say on the topic over a decade since the publication of this journal article. The Journal of Geographical Information Systems publishing since 2009 perhaps satisfies the academic merit GIS would need to be considered a science by some of the forum participators. This said, I would say that Wright’s proposition that the phenomena of GIS is ‘a continuum between tool and science’ rings strong and true today.  My response to the question, you may ask? D. All of the above, GIS is ever evolving, and can’t be placed in a discrete category.

– Othello

Problems of classification

Thursday, April 4th, 2013

Since the paper by Wilkinson in 1996 many satellites have been put into orbits and several million GBs of satellite image have been collected. But more importantly, with the coming of the digital camera there has been an explosion in the amount of digital images that have been captured. Consequently, people were quick to spot the opportunity in leveraging the data from the images; hence a lot of research has been conducted in the image processing domain (mainly in biometrics and security). This being said, some of the most successful approaches in other domains have not been as well, when applied to satellite images. And the  challenges outlined in the paper still hold true today.

According to my understanding this is mainly because of the great diversity in satellite images. The resolution is only one part of the equation. The main problem lies in the diversity of the things being imaged. This makes it very difficult to come up with training samples that are a good fit. Thus, traditional Machine Learning techniques based on supervised learning have a hard time. Moreover, the problem is compounded by the fact that when we are classifying satellite images, we are generally interested in extracting not one, but several classes simultaneously with great accuracy. However, the algorithms do perform well when classification is performed one image at a time but significant human involvement is needed to select good training samples for each image. But to the best of my knowledge no technique exists which can completely automatically classify satellite images.

-Dipto Sarkar

Error prone GIS

Monday, April 1st, 2013

In any data related field great efforts are put into ensuring the quality and integrity of the data being used. It has long been recognized that the quality of results can only be as good as the data itself, moreover, the quality of data is no better than the worst apple in the lot. Hence, for any data intensive field great efforts are put into data pre-processing to understand and improve the quality of the data. GIS is no exception when it comes to being cautious about the data.

The various kinds of data being handled in GIS makes the problem of errors more profound. Not only does GIS work with vector and raster data, it also needs to handle data in forms of tables. Moreover, the way the data is procured and converted is also a concern. Many a times data is obtained from external sources in the form of tables of incidences that have some filed(s) containing the location of the event. Usually this data was not collected with the specific purpose of being analysed for spatial patterns, hence, the location accuracy of the events are greatly varied. Thus, when these files are converted into shapefiles, it inherits the inaccuracy inbuilt in the data-set.

One of the things to remember however is, that the aim of GIS is to abstract reality to a form which can be understood and analysed efficiently. Thus it is important not to lay too much emphasis on how accurately the data fits the real world. The emphasis on the other hand should be to find out the level of abstraction that is ideal for the application scenario and then understand the errors that can be accepted at that level of abstraction.

-Dipto Sarkar

Statutory warning: Geocoding may be prone to errors

Thursday, March 21st, 2013

The last few years have seen tremendous growth in the usage of Spatial Data. Innumerable applications have contributed to the gathering of spatial information from the public. Application’s people use every day like Facebook and Flickr have also introduced features with which one can report their location. However, people are not generally interested in geographic lat-long. Names of places make more sense in a day to day life. Hence, all the applications report not the spatial co-ordinates but the named location (at different scale) where the person is. The tremendous amounts of location information generated have not gone unnoticed and several researches have been conducted to leverage this information. But, one issue that is frequently overlooked in researches that use these locations is the accuracy of the geocoding service that was used to get the named locations. Not only is displacement a problem but scale at which the location was geocoded will also have an effect on the study. The comparison of the various accuracy of the available geocoding services done by Roongpiboonsopit et. al. serves as a warning to anyone using the geocoded results.

-Dipto Sarkar


Radical changes in Time

Wednesday, March 13th, 2013

The paper by Langran et. al. made me realize how little has been achieved in representing the temporal aspect through maps. Digital maps have tried portraying the changes in some phenomenon over time through the use of accessories like time sliders. But this only changes the overlay information on a static base map. The lack of tighter time-map integration makes it impossible to capture the cause and effects in a more holistic way.

Though GIScience emerged as a merger of spatial sciences with technology, it embraced the concept of temporarily static maps to represent data.

The foremost thought that comes to my mind is that a radical change is required in how we represent space-time. The whole concept of maps needs to be redesigned to break the triangle of theme, location and time. Though this may be a very strong statement without much backing, I think with redesign of representation and choosing the right data structure, maps can be made to represent both location and time together, keeping the theme fixed. This will be akin to perceiving the world as a state machine, with a set of states and actions that causes state changes (but the set of states and actions may be potentially infinite and not necessarily be known a priori). The concept of state machine addresses the “root” of the problem, i.e. different snapshots represent the states, but not the events that caused the changes. This however, requires tremendous efforts and change of mind-set coupled with embracing of technology in redesigning the thought process.

– Dipto Sarkar

Maps vs Reality vs Virtual Reality

Thursday, February 28th, 2013

To be very honest, I found the paper by Richardson et. al to be one of the more interesting papers that I have read. The comparisons that they make are intriguing and the results are still more surprising.

I found the experiment designed by the researchers to be very robust. Hence, the results of the experiment can be accepted to be quite accurate. The question that the results raised in my mind was about the effects that augmented reality systems have on our spatial cognition abilities. Considering GPS navigator to be an augmented reality system, does it mean that we are becoming less adept at navigating naturally because we rely on the GPS navigator? Has anyone conducted research to understand the effect GPS navigation systems have on an individual’s spatial cognition abilities? How accurately and efficiently can regular GPS navigator users find out the route between two places compared to non-navigator users?

-Dipto Sarkar


Humans as Sensors

Monday, February 25th, 2013

The paper by Goodchild provides an overview of the various enabling factors that have led to the success of VGIS. I found the concept of “Humans as sensors” to be particularly interesting. I feel that this is has been the primary driving force behind VGIS services like Wikimapia, Openstreet Maps and even Google Maps. When maps started becoming digital, one of the primary challenges was to gather enough data to represent an area at different scales. This problem was not particularly profound in case of paper maps which were produced at certain discrete scales only. To gather enough data for digital maps, mass public participation became inevitable. Collecting so much data at different granularity levels was made possible only because people with varying degree of knowledge about an area started to contribute to services like OpenStreet Maps; overtime generating enough information to provide a fairly complete “patchwork”. Despite all the public effort, Google Maps for India have been criticized to be incomplete, incorrect and even non-existent in certain cases. As a response, Google has organised an event called Mapathon 2013 (from 12th of February 2013 to the 25th of March 2013) in India. The event aims to incentivise the process of adding geographic information to Google Maps by giving out attractive prices to the top editors.

When it comes to the use of VGIS in case of emergency or disaster situations, where traditional data collection can become too slow to be useful, Ushahidi deserves special mention. “Ushahidi (Swahili for “testimony” or “witness”) created a website ( in the aftermath of Kenya’s disputed 2007 presidential election that collected eyewitness reports of violence sent in by email and text-message and placed them on a Google Maps map” (Wikipedia). A visit to the Wikipedia entry for Ushahidi reveals several crisis situations where similar solutions based on the Ushahidi platform proved to be helpful. I also encourage a visit to the Ushahidi website ( to understand the wide range of technological support that it provides to build crisis/disaster mapping portals.

– Dipto Sarkar

Critical GIS

Thursday, February 21st, 2013

I found the paper by O’Sullivan very intriguing. I was completely unaware of the fact that research in GIS is going on in some of the directions mentioned by the paper.  I particularly found the sections ‘Gendering of GIS’ to be very interesting.  In India, there is a lot of work going on in woman empowerment. And it will be very interesting to see whether someone can use similar systems given the limited penetration of the internet.

Privacy and ethics is another part of GIS which does require a lot of research. As more and more applications take into account the location of the user as a principal component, it is becoming very important to come up with standards for privacy protection. With the number of PPGIS applications increasing, a great number of people from the society are contributing to the task of collecting Geographic data. Though this means that GIS is getting higher acceptance in society, it remains a challenge as to how to release this data while striking a balance between accountability and privacy.

-Dipto Sarkar


The near future of Augmented Reality

Monday, February 18th, 2013

After reading the paper by Azuma et. al., I am convinced of the fact that augmented reality systems of the likes shown in Science Fiction Movies are not far. However, I think the first commercial applications of Augmented Reality will use the mobile phones as the primary device. The mobile phones are already equipped with a range of sensors like GPS, Electronic Compass, Accelerometer, Camera, etc. which can be used to provide measurements of the environment. This fact is already leveraged by applications such as Google Goggles and only slight improvements to it will make the system real time, thus making it qualify as an Augmented Reality System according to the definition given by Azuma et. al.  I also feel that acceptance of these applications will be higher as they do not require clunky wearable computers.

Another thought that came to my mind is the use of ubiquitous computing for augmented reality based applications. Instead of putting all the responsibility of sensing the environment, doing calculations and displaying results, it might be useful to distribute some of the task to other smaller specialized units present (or planted) in the physical environment of the user. When a user comes in proximity of these computers, the device they are carrying may just fetch the data and display them after doing some minimal calculations.

-Dipto Sarkar


How to handle scale?

Tuesday, February 12th, 2013

Any discussion in the initial stages of a GIS project has an episode where people argue about what should be the exact scale at which to carry out the analysis. The paper by Danielle J. Marceau gives a great overview of the various ways in which space and scale is conceived and how scales affect the results of analysis. However, many things in nature do repeat themselves very regularly with scale. An entire field of mathematics called Fractals deals with things that are self-similar at different scales. So, a set of formulas can define them very precisely and those formulas are all that is needed to reproduce it at any scale.

So, is it accurate to say that many things in geography appear entirely different at different scales? Or does it change gradually with scale? If so, probably we can view these things as a continuous function of scale. Then it is possible that we will come up with equations that explain this gradual change.  All we would require then will be an equation to describe the process at a particular scale, and another equation to describe how the process changes with scale, and we would be able to reconstruct how the object or phenomenon will look at any required scale.

– Dipto Sarkar

Do Mountains Exist?

Thursday, February 7th, 2013

The deep question with which the paper starts delves into the definitions of existence and comprehension of geographic features around us. The coming of predicate logic was the first attempt to consolidate questions about existence in a scientific framework, thus binding existence to a variable. However, to answer questions about categories and objects, predicate logic faces a challenge as these definitions are by nature recursive. As rightly pointed out by Barry Smith and David M. Mark the question then becomes two folds: “do token entities of a given kind or category K exist?”  and “does the kind or category K itself exist? ”. Predicate logic in itself is good at explaining logical entailment but fails to take into account the how humans perceive things. Thus, it may be right to say that mountains exist as they are part of the perceived environment.

Information Systems on the other hand adopted a different definition of ontologies. It considers ontologies as a set of syntax and semantics to unambiguously describe concepts in a domain. The objects are hence classified by information Systems in to categories and the categories are in turn arranged into a hierarchical structure. However, such an arrangement was futile in describing things like mountains, soils or phenomenon such as gravity. One central goal of ontological regimentation is the resolution of the incompatibilities which result in such circumstances. Hence the concept of fields was developed to efficiently categorize these “things”.

However, there are still doubts with naming of such “things” like mountains. Obviously, Mt. Everest exists because all the particles making Mt. Everest exist but exactly what particles are called Mt. Everest. This is the inherent problem in dealing with fields which are by nature continuous, lacking discrete boundaries.

Ideally the entire field of Ontology should be able to explain the entire set of things which are conceptualized and perceived with no ambiguity. This requires tremendous insight and reflection about why do the things exist in the first place.

– Dipto Sarkar


Statistics and GIS- a lot has changed

Tuesday, February 5th, 2013

A lot has changed in the last 2 decades since the paper on “Spatial Statistical Analysis and Geographic Information Systems” was published by Anselin and Getis. Today, the central focus of GIS is on spatial analysis and the rich set of statistical tools to perform the analysis. Today the GIS database and analysis tools are not looked upon as different software. Spatial analysis is fully integrated in GIS softwares like ArcGIS and QGIS. Furthermore, for very specialized applications, the modular or the loosely coupled approach is often employed. Software like CrimeStat uses data in established GIS Sofware format, perform analysis on them and produce results for use in GIS softwares.

When it comes to the nature of spatial data, two data models have been widely accepted namely Object based model and field/raster based model. Extensive set of analysis tools have been developed for each of them. Data heterogeneity and relation between the objects are also taken into account by slight improvements over these two models.

Exploratory Data Analysis and model driven analysis have progressed hand in hand and complement each other. While new and innovative visualization and exploration tools help in understanding the data and the problem better. Software has evolved over time to perform complex non-linear estimations required for model based analysis.

However, Statistics and GIS is an ever evolving field and newer methodologies and techniques are developed everyday which pushes the boundary of cutting edge research further and further. Newer challenges in statistical analysis include handling Big Data and community generated spatial information. How these new challenges evolve will be very interesting to observe.

-Dipto Sarkar

Geovisualization-What we have achieved

Thursday, January 31st, 2013

Many of the pressing problems of today have a geo-spatial component. The paper by MacEachren rightly points out the challenges in dealing with efficient representation of Geospatial data. In the last 11 years since the paper was written, radical changes have taken place in the domain of virtual mapping. Not only did GIS softwares like ArcGIS and QGIS develop rapidly, other mapping and Virtual Earth services like Google Maps and Google Earth have also become popular. The authors had rightly pointed out the changes that were taking place since the internet became the prominent medium for disseminate geospatial data.

With 80% of all user-generated data on the web containing geo-location information, storing and leveraging this data generates a lot of interest. Some of the problems discussed in the paper have been efficiently dealt with in the recent years. For example, multi-scale representations of objects have been handled with the concept of scale-dependent renderers used extensively in GIS packages as well as in Google Maps and Google Earth. However, the decision of what to show at each scale is still subjective. When Geographic objects are stored in the database as vectors, attribute information can be added to each of the objects to further describe it in a non-spatial manner. The abstraction of layers provide the flexibility of modularising map building and analysis approach, enabling reuse of the layers to create different themes. Crowd Sourcing and mobile mapping applications have defined the way group mapping tasks are performed.

The paper also emphasises several times on the need for cross domain research to address the problem of Geovisualization and spatial analysis. In terms of Geovisualization, research results from the field of Computer Graphics, Geo-sciences, Cartography, Human Computer Interaction and Information Visualization needs to be integrated in order to find new and innovative ways of creating maps. Multi-disciplinary crosscutting research is the way forward to make further advances in how geographic information is presented.

-Dipto Sarkar


Eye-tracking in Augmented Reality

Monday, January 28th, 2013

The paper by Poole et. al. discusses in details the metrics used in eye-tracking research and some of its application. However, the paper failed to mention one of the most successful commercial usage of the technology. Canon introduced SLR cameras from as early as 1992 which employed eye-controlled autofocus. The system worked very well and has led to a lot of discussion amongst photographers as to why Canon does not include this technology in their recent cameras.

Now with the coming of augmented reality systems, eye-tracking technology has the potential to revolutionize how users interact with their surroundings. Ubiquity is the most important requirement for any augmented reality system. Eye-tracking technology can be used to detect when the user seems to be confused and accordingly provide him with contextual information. Such application of augmented reality will be less intrusive and more usable in a day to day life. Eye-tracking technology can be further coupled with other technology such as GPS to make augmented reality systems more usable by increasing the speed at which it detects objects. The location information provided by the GPS can be used to narrow down the search space for the object.  For example, if a tourist is staring at the Eiffel Tower, then the system knows that he is located near the Eiffel Tower in Paris. Hence the search space where the system needs to search for similar looking objects is greatly reduced.

The whole domain of augmented reality is still in its infancy and it is up to the imagination of the engineers to find supplementary technologies that might be used to enhance the system.

– Dipto Sarkar


GIS and Spatial Decision Support Systems

Tuesday, January 22nd, 2013

Decision Support Systems (DSS) are distinguished by the fact that they aid in taking decisions about problems that are semi-structured in their definition. However, they do not replace the decision maker. A DSS have capabilities for handling data, analyzing data and provides muti-dimensional views to help highlight the different aspects of the problem.

One may notice that GISystems are already dealing with the some  of  the things mentioned above. Hence, it may be said that a complete GI suite is quite close to a DSS. The paper by Densham rightly points out that there are however some aspects in which the GISystems lacks from being a complete Spatial Decision Support System.

GIS systems are traditionally meant to handle only spatial data. For a GISystem to be useful as a Spatial DSS, it should have more flexibility in how it handles non-spatial data. Moreover, the outputs of GISystems are usually only cartographic in nature and might not provide some insights about the problems. It is necessary for the system to be able to generates reports, charts and use other data visualization methods to supplement the cartographic maps, thus ensuring a 360 degree view of the situation. A further challenge for simultaneously handling spatial and non-spatial data is to model the complex relationships between them and to come up with algorithms which are able to leverage these relationships.

The paper also proposes a framework for the development of SDSS. The framework leverages the modular approach of building softwares. This approach enables maximum flexibility in terms of re-use of components in building different systems. SDSS toolboxes can be combined into generators, a combination of which can be further configured to produce specific SDSS. This approach not only provides the ease of component re-usability but also facilitates addition of new capabilities to an existing system without disruption.

Densham also emphasizes on the importance of incorporating research results from the fields of DBMS to have a high performance system. The UI of the system needs to be built keeping in mind the fact that the system is going to be used by decision makers who may not be GIS experts. Both the spatial analysis and non-spatial analysis components should be intuitive to use and a variety of outputs ranging from maps to charts to tables must be available in order to highlight all the aspects of the problem.

-Dipto Sarkar